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657 results for “July”
Figure 1 from: Carvalho FL, Magalhães C, Mantelatto FL (2014) Molecular and morphological differentiation between two Miocene-divergent lineages of Amazonian shrimps, with the description of a new species (Decapoda, Palaemonidae, Palaemon). In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 79-108. https://doi.org/10.3897/zookeys.457.6771
Figure 1 - Sample sites of Palaemon carteri, Palaemon ivonicus and Palaemon yuna sp. n. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas; AC-Acre; AM-Amazonas; AP-Amapá; MS-Mato Grosso do Sul; MT-Mato Grosso; PA-Pará and RO-Rondônia.
Figure 7 from: VanMaurik LN, Wortham JL (2014) Grooming as a secondary behavior in the shrimp Macrobrachium rosenbergii (Crustacea, Decapoda, Caridea). In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 55-77. https://doi.org/10.3897/zookeys.457.6292
Figure 7 - Mean total frequency of grooming behaviors of Macrobrachium rosenbergii females (N=21) and male morphotypes (SM: N=28, OC: N=25, BC: N=20) in 30-min time period (mean ± SE). Note: BC = blue-clawed males; F = females, OC = orange-clawed males; SM = small males. No significant differences between the groups, p>0.05.
Figure 3 from: VanMaurik LN, Wortham JL (2014) Grooming as a secondary behavior in the shrimp Macrobrachium rosenbergii (Crustacea, Decapoda, Caridea). In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 55-77. https://doi.org/10.3897/zookeys.457.6292
Figure 3 - Mean frequency of use of grooming appendages of Macrobrachium rosenbergii (N=94) in 30-min time period (mean ± SE). Note: different letters indicate significant differences among use of appendages.
Figure 2 from: VanMaurik LN, Wortham JL (2014) Grooming as a secondary behavior in the shrimp Macrobrachium rosenbergii (Crustacea, Decapoda, Caridea). In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 55-77. https://doi.org/10.3897/zookeys.457.6292
Figure 2 - Relative size of Macrobrachium rosenbergii female and male morphotypes. A Female B Small-clawed (SM) male C Orange-clawed (OC) male D Blue-clawed (BC) male. Note the difference in the size of the chelipeds.
Figure 4 from: VanMaurik LN, Wortham JL (2014) Grooming as a secondary behavior in the shrimp Macrobrachium rosenbergii (Crustacea, Decapoda, Caridea). In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 55-77. https://doi.org/10.3897/zookeys.457.6292
Figure 4 - Mean frequency of use of grooming appendages of Macrobrachium rosenbergii females (N=21) and male morphotypes (SM: N=28, OC: N=25, BC: N=20) in 30-min time period (mean ± SE). Note: BC = blue-clawed males; F = females, OC = orange-clawed males; SM = small males.
The CAR-40 reanalysis dataset during 18-21 July 2021
<p>The CAR-40 reanalysis dataset during 18-21 July 2021</p>
Seawater velocities measured by autonomous sailbuoy Adcp in the Barents Sea from May to July 2021 on campaign the PolarFront project
<p>This dataset contains ocean currents measured by sailing autonomous surface vehicle <em>Adcp</em>, while on campaign at 70–77N in the Barents Sea for the <a href="https://github.com/akvaplan-niva/polarfront">PolarFront</a> research project, from 16 May to 25 July 2021 (Daase 2021). The <em>Adcp</em> is equipped with a <a href="https://www.aanderaa.com/">Aanderaa</a> DCPS 5400 operating at 600 kHz, mounted in the keel at –0.2 m.</p> <p><strong>Space/time coverage</strong></p> <ul> <li>Time: 2021-05-16T13:45:00Z/2021-07-25T13:15:00Z</li> <li>Space: [20.5,70.0,33.0,76.8] ([W,S,E,N])</li> </ul> <p><strong>Data distributions</strong></p> <p><em>Datalogger (text files)</em></p> <p>The primary distribution consists of 2 datalogger text files retrieved post-mission from sailbuoy internal storage. The files are the original full scale original data records, as captured by the internal sofware of manufacturer <a href="http://www.sailbuoy.no/">Offshore Sensing</a>.</p> <ul> <li>DATA.TXT: Position and sensor metadata</li> <li>DCPS.TXT: Ocean currents</li> </ul> <p><em>GeoJSON</em></p> <p>For increased data interoperability, a <a href="https://www.rfc-editor.org/info/rfc7946"><strong>GeoJSON</strong></a> file is also included, consisting of Point features like the following:</p> <p>{ "geometry": { "coordinates": [30.11165, 76.438894], "type": "Point" }, "properties": { "time": "2021-05-19T22:45:00Z", "TTFF": 11, "Count": 24, "Commands": 0, "TxTries": 1, "ONT": 635, "DiskUsed": 0.783123, "Files": 0, "I": 0.01564, "V": 13.195122, "Temperature": 4.06502, "DCPSStatus": 0, "DCPSOnMin": 10, "DCPSSpeed": 0.329999, "DCPSDirection": 233.233643 }, "type": "Feature" }</p> <p>The GeoJSON file is derived from DATA.TXT and contains the full position and DCPS metadata log in a standard/machine-parsable format, including coordinated universal time following <a href="https://datatracker.ietf.org/doc/html/rfc3339">RFC 3339</a>/<a href="https://www.iso.org/obp/ui#iso:std:iso:8601:-1:ed-1:v1:en">ISO 8601</a>.</p> <p><strong>Data formats and interoperability</strong></p> <p>Both of the datalogger text files are in non-standard vendor formats. The DCPS text format is described in the <a href="https://www.aanderaa.com/media/pdfs/td304-manual-dcps.pdf">vendor manual.</a></p> <p><strong>Related publications</strong></p> <p>For a recent discussion on measuring ocean currents from sailbuoys compared to other platforms, see <a href="https://doi.org/10.3390/s22155553">Wullenweber et al., 2022</a>.</p> <p>See also <a href="https://doi.org/10.1029/2019GL086649">Swart et al.,2020</a>; <a href="https://doi.org/10.3390/s21206752">Camus et al., 2021</a> for further discussion on near-surface data collection with sailbuoys and other autonomous vehicles.</p> <p><strong>References</strong></p> <p>Camus L, Andrade H, Aniceto AS, Aune M, Bandara K, Basedow SL, Christensen KH, Cook J, Daase M, Dunlop K, Falk-Petersen S, Fietzek P, Fonnes G, Ghaffari P, Gramvik G, Graves I, Hayes D, Langeland T, Lura H, Kristiansen T, Nøst OA, Peddie D, Pederick J, Pedersen G, Sperrevik AK, Sørensen K, Tassara L, Tjøstheim S, Tverberg V, Dahle S (2021). Autonomous Surface and Underwater Vehicles as Effective Ecosystem Monitoring and Research Platforms in the Arctic—The Glider Project. Sensors 21(20):6752. <a href="https://doi.org/10.3390/s21206752">https://doi.org/10.3390/s21206752</a></p> <p>Daase M (ed.). (2021). ARCTOS Barents Sea Polar Front May 2021 Cruise Report (1.1.0). Zenodo. <a href="https://doi.org/10.5281/zenodo.7384076">https://doi.org/10.5281/zenodo.7384076</a></p> <p>Edholm J. (2022). Sailbuoy DCPS. Zenodo. <a href="https://doi.org/10.5281/zenodo.6798056">https://doi.org/10.5281/zenodo.6798056</a></p> <p>Swart S, du Plessis MD, Thompson AF, Biddle LC, Giddy I, Linders T, Mohrmann M, Nicholson S (2020). Submesoscale fronts in the Antarctic marginal ice zone and their response to wind forcing. Geophysical Research Letters, 47, e2019GL086649. <a href="https://doi.org/10.1029/2019GL086649">https://doi.org/10.1029/2019GL086649</a></p> <p>Wullenweber N, Hole LR, Ghaffari P, Graves I, Tholo H, Camus L (2022). SailBuoy Ocean Currents: Low-Cost Upper-Layer Ocean Current Measurements. Sensors. 22(15):5553. <a href="https://doi.org/10.3390/s22155553">https://doi.org/10.3390/s22155553</a></p>
Ocean eddy kinetic energy at 1000 m depth estimated from Argo drift data from July 1997 to December 2015
<p><strong>Eddy kinetic energy at 1000 dbar depth estimated from Argo drift data from July 1997 to December 2015</strong><br><br>These are the data used to draw Fig.1 of Katsumata (2017b).<br>Argo drift data from YoMaHa (Lebedev et al. 2017) is averaged<br>in a quasi-circle with a radius of 300 km, deformed to follow<br>bathymetry, and deviation from the average is our eddy here.<br><br>Detail of the method is found in Katsumata (2017a).<br><br><a href="https://doi.org/10.1175/JPO-D-16-0150.1">Katsumata (2017a)</a><br><a href="https://doi.org/10.1175/JPO-D-16-0150.1">Katsumata (2017b)</a><br>Lebedev, K., H. Yoshinari, N. A. Maximenko, and P. W. Hacker,<br> (2007) YoMaHa’07: Velocity data assessed from trajectories of<br> Argo floats at parking level and at the sea surface. IPRC Tech.<br> Note 4, 16 pp.<br> <a href="https://doi.org/10.1175/JPO-D-16-0150.1">http://apdrc.soest.hawaii.edu/projects/yomaha/</a></p> <p> </p>
Taiwan electricity generation and demand data, 2017 January - 2022 July
<p>This is Taiwan's electricity generation/demand data from 2017 January to 2022 July, in 10-min resolution.</p> <p>Two files are included so far:</p> <ul> <li>loadarea: the electricity demand in four areas (i.e. north, central, south, east) in Taiwan. The information of the area can be found on <a href="https://www.taipower.com.tw/en/page.aspx?mid=4487&cid=2876&cchk=2c550ab4-907c-45df-822d-f35b4d2c63d0">Taipower's web page</a>.</li> <li>powerRatio: the power of each type of electricity generation. The data include both the generation from Taipower company and IPP (independent power plant); 'lng' is refer to gas power plant.</li> </ul> <p><strong>Source</strong>:</p> <ul> <li>the original data can be obtained from the Taiwanese government's open-data platform data.gov.tw.</li> <li>The link to the corresponding dataset is <a href="https://data.gov.tw/dataset/37331">https://data.gov.tw/dataset/37331</a>. (please note this link can only download 3 months of data that be collected a half year ago)</li> <li>live data can be obtained here (update very 10 min) <a href="https://data.gov.tw/dataset/8931">https://data.gov.tw/dataset/8931</a> with Chinese characters</li> <li>More information can be found on the Taipower webpage of <a href="https://www.taipower.com.tw/en/pageList.aspx">Information Disclosure</a>.</li> </ul> <p><strong>License:</strong></p> <ul> <li><a href="https://data.gov.tw/license">Open Government Data License, version 1.0</a> (Taiwan)</li> </ul>
Throughfall and rain event data, May-July 2014-2016, Hainich, Germany, project AquaDiva
<p>This dataset contains throughfall and gross precipitation data used for the analysis published in Metzger et al. (2017) and Fischer et al. (2023). It gives spatially distributed throughfall evaluated at a rain event scale covering the following periods:</p> <p>May 1 - July 26 2014</p> <p>May 9 - July 28 2015</p> <p>May 24 - August 02 2016</p> <p>The two enclosed files cover the collected throughfall at all sampling points per precipitation event, and the properties of each recorded precipitation event, containing also gross precipitation.</p> <p>The field site, sampling design data collection are described in Metzger et al. (2017) and used in Fischer et al. (2023). The sampling design is given in an associated published dataset Metzger and Hildebrandt (2023). For stemflow measurements on the same site during the same precipitation events, see dataset Metzger and Hildebrandt (2019), cited in Metzger et al. (2019).</p>
Wind July 2013
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Rain and Hail intensity. July 2013
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Rain and Hail intensity. July 2013
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Wind July 2013
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Toxoplasma gondii microscopy and PCR detection results between July, 2020 and August, 2022 in greater Monterey Bay, CA
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Data from: "Blood transcriptome sequencing of Common Crossbills (Loxia curvirostra) experimentally infected by the avian malaria parasite Plasmodium relictum (lineage SGS1)" in Genomic Resources Notes accepted 1 June 2013-31 July 2013
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Data from: "Transcriptomic resources for five shrimp (Crustacea: Atyidae and Alpheidae) species from the anchialine ecosystem" in Genomic Resources Notes accepted 1 June 2014 to 31 July 2014
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Pollinator surveys of two populations located in the North and South of Mallorca (Balearic Islands, Spain) in 2021 from May to July focused on Eryngium maritimum pollinators
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Data from: "You are not what you eat: massive parallel sequencing reveals that gut microbiome is not diet-related in larval Dilophus febrilis (Diptera: Bibionidae)" in Genomic Resources Notes Accepted 1 June 2015 to 31 July 2015
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Nano- and Microplastic Abundance, analyzed with Epifluorescence microscopy, collected aboard two student cruises on two student cruises, SKrillEx I (July 2014) and SKrillEx II (June 2015).
Surface seawater was collected in stainless steel buckets in the nearshore California Current on two student cruises, SKrillEx I (July 2014) and SKrillEx II (June 2015). Surface seawater samples were filtered on to 5-µm pore polycarbonate filters, and frozen at sea for later analysis. Once back on land, the frozen transparent polycarbonate (PC) filters were filtered on an all-glass apparatus and then imaged with modified epifluorescence microscopy techniques for microplastic particles. All microplastic particles were analyzed for plastic shape, length, surface area, and fluorescence.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.